Distributionally Robust Learning
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Distributionally Robust Learning
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Author : Ruidi Chen
language : en
Publisher:
Release Date : 2020-12-23
Distributionally Robust Learning written by Ruidi Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-23 with Mathematics categories.
Wasserstein Distributionally Robust Learning
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Author : OROOSH Shafieezadeh Abadeh
language : en
Publisher:
Release Date : 2020
Wasserstein Distributionally Robust Learning written by OROOSH Shafieezadeh Abadeh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Mots-clés de l'auteur: Distributionally robust optimization ; Wasserstein distance ; Regularization ; Supervised Learning ; Inverse optimization ; Kalman filter ; Frank-Wolfe algorithm.
Mathematical Optimization Theory And Operations Research
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Author : Yury Kochetov
language : en
Publisher: Springer Nature
Release Date : 2025-07-05
Mathematical Optimization Theory And Operations Research written by Yury Kochetov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-05 with Mathematics categories.
This book LNCS 15681 constitutes the refereed proceedings of the 24th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2025, held in Novosibirsk, Russia, during July 7–11, 2025. The 27 full papers were carefully reviewed and selected from 72 submissions. The proceeding focus on Mathematical Programming; Optimal Control; Game Theory; Operations Research and Applications; Machine Learning and Optimization.
Mathematical Optimization Theory And Operations Research
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Author : Michael Khachay
language : en
Publisher: Springer Nature
Release Date : 2023-06-25
Mathematical Optimization Theory And Operations Research written by Michael Khachay and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-25 with Mathematics categories.
This book constitutes the refereed proceedings of the 22nd International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2023, held in Ekaterinburg, Russia, during July 2–8, 2023. The 28 full papers and 1 short paper included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: Mathematical programming and applications; discrete and combinatorial optimization; stochastic optimization; scheduling; game theory; and optimal control and mathematical economics. The book also contains one invited talk in full paper length.
Iot For Defense And National Security
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Author : Robert Douglass
language : en
Publisher: John Wiley & Sons
Release Date : 2023-01-04
Iot For Defense And National Security written by Robert Douglass and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-04 with Political Science categories.
IoT for Defense and National Security Practical case-based guide illustrating the challenges and solutions of adopting IoT in both secure and hostile environments IoT for Defense and National Security covers topics on IoT security, architecture, robotics, sensing, policy, operations, and more, including the latest results from the premier IoT research initiative of the U.S. Defense Department, the Internet of Battle Things. The text also discusses challenges in converting defense industrial operations to IoT and summarizes policy recommendations for regulating government use of IoT in free societies. As a modern reference, this book covers multiple technologies in IoT including survivable tactical IoT using content-based routing, mobile ad-hoc networks, and electronically formed beams. Examples of IoT architectures include using KepServerEX for edge connectivity and AWS IoT Core and Amazon S3 for IoT data. To aid in reader comprehension, the text uses case studies illustrating the challenges and solutions for using robotic devices in defense applications, plus case studies on using IoT for a defense industrial base. Written by leading researchers and practitioners of IoT technology for defense and national security, IoT for Defense and National Security also includes information on: Changes in warfare driven by IoT weapons, logistics, and systems IoT resource allocation (monitoring existing resources and reallocating them in response to adversarial actions) Principles of AI-enabled processing for Internet of Battlefield Things, including machine learning and inference Vulnerabilities in tactical IoT communications, networks, servers and architectures, and strategies for securing them Adapting rapidly expanding commercial IoT to power IoT for defense For application engineers from defense-related companies as well as managers, policy makers, and academics, IoT for Defense and National Security is a one-of-a-kind resource, providing expansive coverage of an important yet sensitive topic that is often shielded from the public due to classified or restricted distributions.
Advances And Trends In Artificial Intelligence Theory And Applications
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Author : Hamido Fujita
language : en
Publisher: Springer Nature
Release Date : 2025-08-01
Advances And Trends In Artificial Intelligence Theory And Applications written by Hamido Fujita and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-01 with Computers categories.
This book constitutes the refereed proceedings of the 38th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems on Advances and Trends in Artificial Intelligence, IEA/AIE 2025, held in Kitakyushu, Japan, in July 1–4, 2025. The 80 full papers and 9 short papers included in this book were carefully reviewed and selected from 130 submissions. They focus on the following topical sections: Part I: Reinforcement Learning; Optimization; Natural Language Processing; Multi-Agent; Machine Learning and Decision Making; Knowledge Representation; Data Engineering; Large Language Model; Computer Vision. Part II: Robotics; Education; Cyber Security; Healthcare and Medical Applications; Advanced Applied Intelligence Methodologies and Applications; Intelligent Systems and e-Applications; Industrial and Engineering Applications.
Machine Learning For Engineers
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Author : Osvaldo Simeone
language : en
Publisher: Cambridge University Press
Release Date : 2022-11-03
Machine Learning For Engineers written by Osvaldo Simeone and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-03 with Computers categories.
This self-contained introduction contains all students need to start applying machine learning principles to real-world engineering problems.
Modern Trends In Controlled Stochastic Processes
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Author : Alexey Piunovskiy
language : en
Publisher: Springer Nature
Release Date : 2021-06-04
Modern Trends In Controlled Stochastic Processes written by Alexey Piunovskiy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-04 with Technology & Engineering categories.
This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference.
Financial Signal Processing And Machine Learning
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Author : Ali N. Akansu
language : en
Publisher: John Wiley & Sons
Release Date : 2016-05-31
Financial Signal Processing And Machine Learning written by Ali N. Akansu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-31 with Technology & Engineering categories.
The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.
Applied Modeling Techniques And Data Analysis 1
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Author : Yiannis Dimotikalis
language : en
Publisher: John Wiley & Sons
Release Date : 2021-05-11
Applied Modeling Techniques And Data Analysis 1 written by Yiannis Dimotikalis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-11 with Business & Economics categories.
BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.